A new control approach for automated drifting in consideration of the driving characteristics of an expert human driver. (March 2020) - Joa, Eunhyek; Cha, Hyunsoo; Hyun, Youngjin; Koh, Youngil; Yi, Kyongsu; Park, Jaeyong
Abstract: This paper presents a new control approach for automated drifting in consideration of how expert drivers conduct drifting. The expert drivers stabilize their vehicles at high sideslip angle using not prior knowledge of tire dynamics and equilibrium but current vehicle states. By mimicking how these expert drivers control their vehicles at high sideslip angle, the proposed controller is able to control the vehicle at high sideslip angle using only current vehicle states, i.e without prior knowledge of tire and drift equilibria. Specifically, the proposed controller can perform steady state drifting without the knowledge of the equilibrium of the vehicle system. The proposed controller consists of three consecutive parts. First, the supervisor determines the desired yaw rate and rear longitudinal slip ratio. Second, the upper-level controller calculates the desired front lateral force and rear longitudinal force to track the desired motions. Third, the lower-level controller converts the upper-level controller's desired forces into steering wheel angle and gas pedal input, which are actual control inputs of vehicles. The proposed algorithm has been investigated via vehicle tests. A rear wheel driven mid-sized vehicle with limited slip differential and internal combustion engine was utilized for testbed. The test results indicate that the proposed algorithm can successfully conduct automated drift maneuvers. Furthermore, the stability of the closed-loop drift control system has been proved by using Lyapunov stability analysis and estimating Region of Attraction (RoA). The vehicle test results are superimposed on the estimate of RoA, and it has been shown that vehicle states within the estimate of RoA converge well to the desired motions. In addition, the comparison of the proposed algorithm with the previously developed drifting control algorithm was conducted. In contrast to the drifting control algorithm that was based on drift equilibrium, the proposed control algorithm is capable of conducting drift maneuvers on both high friction roads and low friction roads without prior knowledge of the tire model and road friction coefficient. Highlights: A new approach for automated drifting without knowing the equilibrium of the system. Validate the proposed algorithm via vehicle tests with engine-powered vehicle. Translate expert drivers' behavior and instructions into control strategies. The equilibrium of the closed-loop system is locally asymptotically stable.